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undergraduate thesis
Primjena umjetne inteligencije u inženjerstvu materijala
Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology, 2022. urn:nbn:hr:149:027593
Miškulin, Tea
University of Zagreb
Faculty of Chemical Engineering and Technology

Institutional repository: Repository of Faculty of Chemical Engineering and Technology University of Zagreb

Cite this document

Miškulin, T. (2022). Primjena umjetne inteligencije u inženjerstvu materijala (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology. Retrieved from https://urn.nsk.hr/urn:nbn:hr:149:027593

Miškulin, Tea. "Primjena umjetne inteligencije u inženjerstvu materijala." Undergraduate thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2022. https://urn.nsk.hr/urn:nbn:hr:149:027593

Miškulin, Tea. "Primjena umjetne inteligencije u inženjerstvu materijala." Undergraduate thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2022. https://urn.nsk.hr/urn:nbn:hr:149:027593

Miškulin, T. (2022). 'Primjena umjetne inteligencije u inženjerstvu materijala', Undergraduate thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, accessed 26 November 2024, https://urn.nsk.hr/urn:nbn:hr:149:027593

Miškulin T. Primjena umjetne inteligencije u inženjerstvu materijala [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology; 2022 [cited 2024 November 26] Available at: https://urn.nsk.hr/urn:nbn:hr:149:027593

T. Miškulin, "Primjena umjetne inteligencije u inženjerstvu materijala", Undergraduate thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:149:027593

Metadata
TitlePrimjena umjetne inteligencije u inženjerstvu materijala
Title (english)AI applications in materials science
AuthorTea Miškulin
MentorMiroslav Jerković (mentor)
Committee memberMiroslav Jerković (predsjednik povjerenstva)
Committee memberNenad Bolf (član povjerenstva)
Committee memberIva Movre Šapić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Chemical Engineering and Technology
Zagreb
Defense date and country2022-09-14, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Beton je jedan od najstarijih materijala kojeg ljudi koriste, a danas je najvažniji materijal u građevinskom inženjerstvu. Kroz godine razvijali su se novi načini proizvodnje betona koji su pomogli stvaranju snažnijeg i izdržljivijeg betona. Beton je mješavina različitih sastojaka, a njegova čvrstoća određuje sveukupnu kvalitetu mješavine. Za ocjenu kvalitete betona najčešće se koristi tlačna čvrstoća. Na čvrstoću, osim cementa, utjecaj imaju i mnogi drugi sastojci poput šljake, letećeg pepela, vode, superplastifikatora, krupnih agregata, finih agregata, ali i starost. Tlačna čvrstoća betona funkcija je starosti i sastojaka betona. Kako bi analiza utjecaja ovih parametara na čvrstoću bila što jednostavnija primjenjuju se različiti algoritmi umjetne inteligencije koji procjenjuju vrijednost čvrstoće. Za primjenu algoritama koristi se programski jezik R, kao jedan od najčešće korištenih programskih jezika za rješavanje problema zbog svoje jednostavnosti i pristupačnosti. Cilj ovog rada je implementacijom algoritama umjetne inteligencije pronaći model koji najbolje procjenjuje tlačnu čvrstoću betona.
Abstract (english)
Concrete is one of the oldest materials that people use, and today is the most important material used in civil engineering. Throughout the years, new methods of concrete production have been developed that have helped to create stronger and more durable concrete. Concrete is a mixture of many different ingredients, and its strength determines the overall quality of the mixture. Compressive strength is most often used to evaluate the quality of concrete. In addition to cement, strength is also influenced by many other ingredients such as slag, fly ash, water, superplasticizers, coarse aggregate, fine aggregate, and also age. The compressive strength of concrete is a function of age and its ingredients. In order to make the analysis of the impact of these parameters on the compressive strength as simple as possible, various artificial intelligence algorithms are applied to estimate the strength value. To apply the algorithms, the R programming language is used, as it is on of the most commonly used programming languages for solving problems due to its simplicity and accesibility. The goal of this work is to find a model that best estimates the compressive strength of concrete by implementing artificial intelligence algorithms.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:149:027593
Study programmeTitle: Chemical Engineering - Undergraduate study
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka kemijskog inženjerstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka kemijskog inženjerstva)
Type of resourceText
File originBorn digital
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Created on2023-03-08 13:26:18